Abstract 2859: Understanding metastatic cancer biology

Abstract

Abstract Introduction: Metastatic disease is responsible for 90% of all cancer death. Understanding the process of how primary tumors achieve metastatic potential is of great importance and paramount to the development of precision medicine that may limit the aggressive distant spread of metastatic cancer. It is hypothesized that during cancer evolution, cells within the primary tumor obtain metastatic potential through acquisition of specific somatic alterations. However, the defining ability that allows metastasis remains unknown. By comparing genomic profiles of primary and metastatic cancers we wish to investigate if potential metastatic gate-keeper mutations exist, defined as alterations to individual genes or pathways that are required to facilitate metastatic dissemination. Material and methods: Here, we analyzed panel-based DNA sequencing datasets from the GENIE (Genomics Evidence Neoplasia Information Exchange) project. Analyses were performed on 123 shared genes from the 6 most common panels, selected to include as many patients as possible while analyzing as many genes as possible. In total 43,323 patients had mutations in one or more of the 123 shared genes across 37 different cancer types. Using bioinformatic tools, we compared genomic alterations in primary versus metastatic samples. Results: Out of the 123 genes we found 26 significantly enriched genes and 30 significantly depleted genes in metastatic disease in at least one cancer type. Overall, TP53 was the most mutated gene across all cancer types and the most enriched gene with significant enrichment in metastatic prostate cancer, non-small cell lung cancer and soft tissue sarcoma. Out of the 30 depleted genes we identified CTNBB1 as significantly depleted in four different cancer types and PIK3CA significantly depleted in two. PIK3CA is one of the most commonly mutated cancer genes, and a target of several precision therapies. Finding of the gene being depleted may indicate a less significant role in the development of metastatic disease. Additionally, we found a higher tumor mutation burden and increased levels of chromosomal instability for metastatic samples compared to primary. Conclusions: With this analysis we demonstrate how the power of large datasets can be utilized to make novel inferences on cancer biology. We observed significant enrichment in overall mutation counts and copy number alterations. Furthermore, we identified both enrichments and depletions of specific alterations in metastatic disease potentially revealing how certain driver gene combinations associate with cancer progression more commonly than others. Citation Format: Ditte Sigaard Christensen, Johanne Ahrenfeldt, Nicolai Juul Birkbak. Understanding metastatic cancer biology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2859.